Predictive Shipment Visibility Platform Built for a US Freight Broker

Overview

We built an AI predictive shipment visibility platform for a mid-size US logistics broker, replacing static, rule-based ETA tracking with real-time predictive intelligence. In 10 weeks, we moved the client from reactive, call-and-email visibility to a proactive transportation visibility platform that flags at-risk shipments before they miss SLA, giving ops and CX teams a head start instead of a fire to put out.

Our Solution

Real-Time Ingestion Layer

We built an Ingestion Agent that subscribes to live GPS and ELD telematics streams instead of polling on a fixed interval. Every position update, delay signal, and lane change flows into a real-time shipment context the moment it happens, forming the backbone of a true real time shipment tracking system.

AI-Driven ETA Prediction

An ETA Agent, running on XGBoost and LightGBM models, replaced the static distance-and-speed formula. As a predictive ETA software layer, it factors in live traffic, historical carrier behavior, route, and current speed to produce a continuously updated ETA with a confidence score, not a one-time guess.

Dynamic Risk Scoring

A Risk Scoring Agent evaluates every active shipment against dwell time, weather conditions, and ETA drift, then assigns a live risk level instead of waiting for a rule threshold to trip after the fact. This is the core of the platform's predictive analytics for logistics capability.

Proactive, Context-Aware Alerting

Instead of a static "status changed to delayed" notification, our Alerting Agent pushes context-aware alerts, ETA changes, and risk flags to dispatch and CX through Slack, email, and the dashboard, before the delay actually happens.

Automated Escalation Handling

When a shipment's risk crosses a set threshold, an Escalation Agent generates a rationale and a recommended next step for the ops team automatically, so escalations start with a plan instead of a scramble. This is what makes the system genuinely useful as AI for freight brokers managing high shipment volumes.

Unified Visibility Dashboard

A React and Tailwind CSS dashboard gives ops, CX, and leadership a single, color-coded view of every load in transit, with filterable status, live map tracking, and drill-down into individual shipment events, functioning as a complete logistics visibility platform for daily operations.

Key Features

What the AI Predictive Visibility Platform Delivers

From raw telematics data to proactive, actionable risk alerts

Real-Time Shipment Tracking

Ingests live location data from ELDs, telematics, and TMS platforms instead of relying on periodic check calls, giving ops a genuine AI freight tracking view of every load in real time.

AI-Powered ETA Forecasting

XGBoost and LightGBM models predict arrival times using live traffic, weather, and carrier history, updated continuously rather than calculated once, making it a true predictive ETA software solution.

Dynamic Risk Scoring

Every shipment gets a live risk score based on dwell patterns, weather, and ETA drift, with severity levels ops can act on immediately.

Proactive Multi-Channel Alerts

Notifications reach dispatch and CX through Slack, email, or the dashboard before a delay turns into a missed SLA.

Automated Escalation Workflows

High-risk shipments get an auto-generated summary and recommended action, cutting the time between "something's wrong" and "here's what to do."

Color-Coded Shipment Dashboard

A single, responsive view of every load, filterable by status and risk level, replacing scattered spreadsheets and inboxes with one transportation analytics platform.

TMS and ELD Integration

Built to connect with existing systems like MercuryGate and Blue Yonder over REST APIs, so the client did not have to rip out their existing stack.

Secure Multi-User Access

Role-based login through Auth0 lets ops, CX, and leadership access the same freight visibility platform without compromising data security, extending the tool into a broader supply chain visibility solution the whole team can rely on.

Technology Stack

Built with Modern Tech

We leverage cutting-edge technologies to build scalable, secure, and high-performance applications that grow with your business.

ReactJS

Tailwind CSS

FastAPI

PostgreSQL

scikit-learn

XGBoost

LightGBM

Auth0

AWS

Slack API

REST APIs

Business Impact

Measurable Results

Real outcomes that transformed our client's operations and delivered significant ROI.

42%

Reduction in SLA Misses

Predictive alerts enabled teams to resolve delivery risks before SLA deadlines were missed.

58%

Fewer Customer Escalations

Customers received proactive updates before delays became service issues.

68%

Less Time on Manual Tracking

Automated tracking eliminated most carrier follow-ups and manual status checks.

91%

ETA Prediction Accuracy

Improved ETA accuracy from 72% to 91% using AI-driven predictions.

$620K

Annual Savings

Lower penalties, fewer expedited shipments, and reduced operational overhead.

30,000+

Loads Monitored Monthly

Every active shipment was tracked with live visibility and AI-powered risk analysis.

8-10 Weeks

Delivery Timeline

Designed, integrated, tested, and deployed within ten weeks.

5

AI Agents Deployed

Ingestion, ETA Prediction, Risk Scoring, Alerting, and Escalation agents work together as one connected AI logistics solution.

Our Process

Project Delivery Approach

A proven methodology that ensures quality delivery, on time and on budget.

Discovery & Static Dashboard (Week 1)

Mapped the client's existing TMS/ELD stack and shipment workflows, then shipped a demo-ready static dashboard with hardcoded shipment statuses, color-coded alerts, and a mobile-responsive layout, giving the team something real to react to from day one.

Backend & Data Pipeline Setup (Weeks 2-4)

Built the FastAPI backend, PostgreSQL schema for shipments and alerts, and mock GPS/CSV ingestion to simulate real-time updates ahead of live integration.

AI Model Development (Weeks 4-6)

Trained the ETA prediction and risk scoring models on historical and live shipment data, tuning for accuracy across the client's specific lanes and carrier mix.

Alerting, Escalation & Live Integration (Weeks 6-8)

Connected the Alerting and Escalation Agents to Slack and email, wired up live TMS/ELD data feeds, and layered in Auth0 for secure multi-user access.

Testing, Hardening & Go-Live (Weeks 8-10)

Ran the system against live shipment volume, tuned risk thresholds with the ops team, and rolled it out fully, with support during the first weeks of live use.